[Paper Review] Throughput Maximization for UAV-Enabled Wireless Powered Communication Networks

Lifeng Xie, Jie Xu+1 more|arXiv (Cornell University)|Jan 14, 2018

Energy Harvesting in Wireless Networks35 references16 citations

TL;DR

This paper proposes a UAV-enabled wireless powered communication network (WPCN) that maximizes uplink common throughput by jointly optimizing UAV trajectory and wireless resource allocation. By exploiting UAV mobility to hover above users for efficient downlink energy transfer and uplink transmission, the scheme significantly outperforms conventional fixed-AP WPCNs, especially in resolving the 'doubly near-far' fairness problem.

ABSTRACT

This paper studies an unmanned aerial vehicle (UAV)-enabled wireless powered communication network (WPCN), in which a UAV is dispatched as a mobile access point (AP) to serve a set of ground users periodically. The UAV employs the radio frequency (RF) wireless power transfer (WPT) to charge the users in the downlink, and the users use the harvested RF energy to send independent information to the UAV in the uplink. Unlike the conventional WPCN with fixed APs, the UAV-enabled WPCN can exploit the mobility of the UAV via trajectory design, jointly with the wireless resource allocation optimization, to maximize the system throughput. In particular, we aim to maximize the uplink common (minimum) throughput among all ground users over a finite UAV's flight period, subject to its maximum speed constraint and the users' energy neutrality constraints. The resulted problem is non-convex and thus difficult to be solved optimally. To tackle this challenge, we first consider an ideal case without the UAV's maximum speed constraint, and obtain the optimal solution to the relaxed problem. The optimal solution shows that the UAV should successively hover above a finite number of ground locations for downlink WPT, as well as above each of the ground users for uplink communication. Next, we consider the general problem with the UAV's maximum speed constraint. Based on the above multi-location-hovering solution, we first propose an efficient successive hover-and-fly trajectory design, jointly with the downlink and uplink wireless resource allocation, and then propose a locally optimal solution by applying the techniques of alternating optimization and successive convex programming (SCP). Numerical results show that the proposed UAV-enabled WPCN achieves significant throughput gains over the conventional WPCN with fixed-location AP.

Motivation & Objective

• To address the 'doubly near-far' problem in conventional WPCNs with fixed APs, where distant users suffer from low energy harvesting and high uplink transmit power.
• To exploit UAV mobility for improved energy transfer and communication fairness by enabling dynamic positioning via trajectory optimization.
• To maximize the minimum (common) uplink throughput among all ground users over a finite flight period.
• To jointly optimize UAV trajectory, downlink WPT, and uplink WIT resource allocation under UAV speed and user energy neutrality constraints.

Proposed method

• Proposes a successive hover-and-fly trajectory design based on the optimal multi-location-hovering solution derived for the unconstrained case.
• Applies alternating optimization and successive convex programming (SCP) to solve the non-convex optimization problem with UAV speed and energy neutrality constraints.
• Uses first-order Taylor approximation to convexify non-convex terms in the downlink and uplink rate expressions.
• Models the UAV’s trajectory as a sequence of hovering phases above ground users and intermediate waypoints to balance energy harvesting and information transmission.
• Implements a two-phase optimization: first, derive the optimal trajectory without speed limits; second, adapt it to include speed constraints via iterative refinement.
• Integrates downlink power and time allocation with uplink transmission scheduling to maximize system fairness and throughput.

Experimental results

Research questions

• RQ1 How can UAV mobility be leveraged to improve energy harvesting and uplink throughput in WPCNs?
• RQ2 What is the optimal trajectory structure for a UAV serving multiple ground users in a WPCN with energy neutrality constraints?
• RQ3 How does the inclusion of UAV speed constraints affect the optimal trajectory and system performance?
• RQ4 Can a successive convex programming approach effectively solve the non-convex joint optimization of UAV trajectory and resource allocation?
• RQ5 To what extent does the proposed UAV-enabled WPCN outperform conventional fixed-AP WPCNs in terms of fairness and throughput?

Key findings

• The optimal trajectory without speed constraints involves the UAV successively hovering above a finite number of ground locations and each user, maximizing energy transfer and uplink throughput.
• The proposed successive hover-and-fly trajectory design with SCP-based optimization achieves high performance even under UAV speed constraints.
• Numerical results show significant throughput gains over conventional WPCNs with fixed APs, especially in resolving the doubly near-far fairness issue.
• The UAV-enabled WPCN achieves higher common throughput than a fixed AP, even when the fixed AP is optimally placed.
• The proposed method converges efficiently and provides a locally optimal solution with strong practical feasibility.